INDSTOCH

Individual stochasticity and population heterogeneity in plant and animal demography

Coordinatore	UNIVERSITEIT VAN AMSTERDAM    more Spiacenti, non ci sono informazioni su questo coordinatore. Contattare Fabio per maggiori infomrazioni, grazie.
Nazionalità Coordinatore	Netherlands [NL]
Totale costo	1˙496˙655 €
EC contributo	1˙496˙655 €
Programma	FP7-IDEAS-ERC Specific programme: "Ideas" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
Code Call	ERC-2012-ADG_20120314
Funding Scheme	ERC-AG
Anno di inizio	2013
Periodo (anno-mese-giorno)	2013-06-01   -   2018-05-31

 Partecipanti

#	participant	country	role	EC contrib. [€]
1	UNIVERSITEIT VAN AMSTERDAM  Organization address address: SPUI 21 city: AMSTERDAM postcode: 1012WX contact info Titolo: Dr. Nome: Hal Cognome: Caswell Email: send email Telefono: +31 20 525 6635 Fax: +31 20 525 7832	NL (AMSTERDAM)	hostInstitution	1˙496˙655.00
2	UNIVERSITEIT VAN AMSTERDAM  Organization address address: SPUI 21 city: AMSTERDAM postcode: 1012WX contact info Titolo: Ms. Nome: Birgitta Cognome: Van Wijnen Email: send email Telefono: +31 20 5257217	NL (AMSTERDAM)	hostInstitution	1˙496˙655.00

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 Obiettivo del progetto (Objective)

'Variation among individuals in reproduction, survival, and other demographic traits, is universal. It has two potential sources: heterogeneity (differences among individuals in their vital rates) and individual stochasticity (random differences resulting from the application of the same vital rates to identical individuals). The goal of the proposed research is to incorporate individual stochasticity and heterogeneity into demographic models for plants, animals, and humans. The project has three components: (1) a study of variation in longevity, focusing on perturbation analysis of Markov chain models for mortality, (2) an analysis of the reward structure of populations, to quantify individual stochasticity in reproduction and other properties, and (3) the development of models to incorporate heterogeneity and stochasticity into branching process models and diffusion models. These three topics will be integrated using matrix population models, integrodifference equation models, and Markov chain models for the life cycle.'